Gender bias in your product is a design problem.
Design problems have solutions.

Gender bias in health AI happens when a digital health product or clinical algorithm works less accurately for women than for men. It can enter at any stage: the clinical studies the product is based on, the data it was trained on, the symptoms it describes, or the way it was tested. The result: algorithms that miss symptoms, misclassify risk, or recommend inadequate treatments — specifically for women. It is not an inevitable feature of technology. It is a correctable design flaw.

A gender bias audit for health AI is a structured clinical review that identifies where a digital health product underperforms for women. The output is a report with every finding explained in plain language, ranked by severity, with a prioritized roadmap. WTFog audits are signed by Teresa Hernández, MD.

Because most validation processes measure average performance across the full population. A model with 90% global accuracy can be significantly less accurate for women — and that gap stays invisible until it causes harm. Without sex-disaggregated analysis built into the validation process, bias doesn't get detected. It gets deployed.

Teresa reviews your product documentation and asks the questions a clinical committee would ask: Were the clinical studies behind this product conducted on women as well as men? Was the product tested on women — and were results analysed separately? Does it describe how conditions present differently in women? You share the documentation; Teresa does the rest. No engineering background required on your side.

WTFog works with healthtech founders, product teams, and health AI companies that want their products to perform equitably across their full patient population — and to meet the evidence standards required for clinical adoption, investment, and EU regulatory compliance.

Yes. Under the EU AI Act (Regulation 2024/1689), diagnostic AI systems are classified as high-risk. High-risk AI systems must demonstrate that bias has been assessed and mitigated across demographic groups, including sex and gender. Healthtech companies that don't address this before August 2026 face compliance gaps at deployment.